Dataset Information

Serotyping of sub-Saharan Africa Salmonella strains isolated from poultry feces using multiplex PCR and whole genome sequencing.

ABSTRACT:

Background

Salmonella enterica remains a leading cause of food-borne diseases worldwide. Serotype information is important in food safety and public health activities to reduce the burden of salmonellosis. In the current study, two methods were used to determine serotypes of 111 strains of Salmonella isolated from poultry feces in Burkina Faso. First, Salmonella Multiplex Assay for Rapid Typing (SMART) Polymerase Chain Reaction (PCR) was used to determine the serovars of the S. enterica isolates. Second, serovar prediction based on whole genome sequencing (WGS) data was performed using SeqSero 2.0.

Results

Among the 111 Salmonella isolates, serotypes for 17 (15.31%) isolates were identified based on comparison to a panel of representative SMART codes previously determined for the 50 most common serovars in the United States. Forty-four (44) new SMART codes were developed for common and uncommon serotypes. A total of 105 (94.59%) isolates were serotyped using SeqSero 2.0 for serovar prediction based on WGS data.

Conclusion

We determined that SeqSero 2.0 was more comprehensive for identifying Salmonella serotypes from Burkina Faso than SMART PCR.

SUBMITTER: Kagambega A

PROVIDER: S-EPMC7814607 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Serotyping of sub-Saharan Africa Salmonella strains isolated from poultry feces using multiplex PCR and whole genome sequencing.

Kagambèga Assèta A Hiott Lari M LM Boyle David S DS McMillan Elizabeth A EA Sharma Poonam P Gupta Sushim K SK Ramadan Hazem H Cho Sohyun S Humayoun Shaheen B SB Woodley Tiffanie A TA Barro Nicolas N Jackson Charlene R CR Frye Jonathan G JG

BMC microbiology 20210119 1

<h4>Background</h4>Salmonella enterica remains a leading cause of food-borne diseases worldwide. Serotype information is important in food safety and public health activities to reduce the burden of salmonellosis. In the current study, two methods were used to determine serotypes of 111 strains of Salmonella isolated from poultry feces in Burkina Faso. First, Salmonella Multiplex Assay for Rapid Typing (SMART) Polymerase Chain Reaction (PCR) was used to determine the serovars of the S. enterica ...[more]

PMID: 33468047

Similar Datasets

Project description:Until recently, traditional serology and the Kauffmann White Scheme (KWS) have been the gold standard for Salmonella serotyping. Whole Genome Sequencing (WGS) has now emerged as an alternative in this field. Serotype information remains a cornerstone in food safety and public health activities to reduce the burden of salmonellosis. At the same time, recent advances in WGS have improved the ability to perform advanced pathogen characterization while improving trace back investigations to determine the source of foodborne illness during outbreaks. Serovar prediction based on WGS can be performed using in silico data analysis tools. Three such tools have been developed: (a). Salmonella in silico Typing Resource (SISTR), (b). SeqSero, and (c). in silico 7-gene MLST ST (Multilocus Sequence Typing Sub-Typing) which was generated using the SISTR platform. Public health officials around the world are diligently working to validate these tools for replacing traditional surveillance methods to provide a more powerful approach for molecular epidemiology in support of public health investigations. In this study, we report a retrospective analysis of our laboratory inventory of 1,041 Salmonella isolates collected between 1999 and 2017. These isolates are of public health significance since they all came from either food, feed or environmental swabs. They were all serotyped by both traditional serology and WGS using an in silico SeqSero tool for serovar prediction. Both predicted identical Salmonella serotypes in 899 isolates (86.4% of the 1,041 Salmonella isolates). SeqSero assignments differed from traditional serological testing in 80 isolates (7.7%) and no serotype prediction was ascertained from 62 isolates (5.9%). This retrospective study is an excellent example of using WGS and SeqSero as a data analysis tool to predict Salmonella serotypes that can provide numerous advantages including molecular and genetic details regarding the characteristics of the Salmonella isolates compared to traditional KWS serotyping. In conclusion, it is evident that using WGS and in silico tools for Salmonella serotyping might someday replace traditional serotyping.

Project description:BackgroundPneumococcal serotype identification is essential to monitor pneumococcal vaccine effectiveness and serotype replacement. Serotyping by conventional serological methods are costly, labour-intensive, and require significant technical expertise. We compared two different molecular methods to serotype pneumococci isolated from the nasopharynx of South African infants participating in a birth cohort study, the Drakenstein Child Health Study, in an area with high 13-valent pneumococcal conjugate vaccine (PCV13) coverage.MethodsA real-time multiplex PCR (rmPCR) assay detecting 21 different serotypes/-groups and a sequetyping assay, based on the sequence of the wzh gene within the pneumococcal capsular locus, were compared. Forty pneumococcal control isolates, with serotypes determined by the Quellung reaction, were tested. In addition, 135 pneumococcal isolates obtained from the nasopharynx of healthy children were tested by both serotyping assays and confirmed by Quellung testing. Discordant results were further investigated by whole genome sequencing of four isolates.ResultsOf the 40 control isolates tested, 25 had a serotype covered by the rmPCR assay. These were all correctly serotyped/-grouped. Sequetyping PCR failed in 7/40 (18%) isolates. For the remaining isolates, sequetyping assigned the correct serotype/-group to 29/33 (88%) control isolates. Of the 132/135 (98%) nasopharyngeal pneumococcal isolates that could be typed, 69/132 (52%) and 112/132 (85%) were assigned the correct serotype/-group by rmPCR and sequetyping respectively. The serotypes of 63/132 (48%) isolates were not included in the rmPCR panel. All except three isolates (serotype 25A and 38) were theoretically amplified and differentiated into the correct serotype/-group with some strains giving ambigous results (serotype 13/20, 17F/33C, and 11A/D/1818F). Of the pneumococcal serotypes detected in this study, 69/91 (76%) were not included in the current PCV13. The most frequently identified serotypes were 11A, 13, 15B/15C, 16F and 10A.ConclusionThe rmPCR assay performed well for the 21 serotypes/-groups included in the assay. However, in our study setting, a large proportion of serotypes were not detected by rmPCR. The sequetyping assay performed well, but did misassign specific serotypes. It may be useful for regions where vaccine serotypes are less common, however confirmatory testing is advisable.

Dataset Information

Serotyping of sub-Saharan Africa Salmonella strains isolated from poultry feces using multiplex PCR and whole genome sequencing.

Background

Results

Conclusion

Publications

Serotyping of sub-Saharan Africa Salmonella strains isolated from poultry feces using multiplex PCR and whole genome sequencing.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets